Wood Combustion in an Overfeed Packed Bed, Including Detailed

Feb 15, 2010 - detailed numerical model of packed bed char combustion is extended by the ... Packed bed combustion is widely used for wood waste and...
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Energy Fuels 2010, 24, 1584–1591 Published on Web 02/15/2010

: DOI:10.1021/ef901206d

Wood Combustion in an Overfeed Packed Bed, Including Detailed Measurements within the Bed Elisabeth Girgis† and William L. H. Hallett*,‡ †

Departments of Chemical Engineering and ‡Mechanical Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5 Received October 22, 2009. Revised Manuscript Received January 19, 2010

Measurements of local gas and tar concentrations, temperatures, and properties of samples of bed solids are reported for wood combustion in an overfeed packed bed. A novel probe is introduced for the measurement of tar concentrations in situ, which collects tar samples on small filter elements. It is shown to give credible values of local tar concentrations at different locations in the bed. Particle sizes and properties are measured by analysis of samples from the bed materials taken after shut-down. A previously developed detailed numerical model of packed bed char combustion is extended by the addition of a one-step pyrolysis reaction and compared with experimental measurements. The model is shown to give good agreement with measured quantities using physically reasonable values of the pyrolysis reaction rate parameters.

temperatures and exit product compositions are measured.1-12 This simulates in simplified form the processes taking place locally in a traveling grate or inclined grate stoker. (A few experimental measurements have actually been done in industrial-scale stokers.4) The laboratory bed is typically confined within a cylindrical vessel of 10-30 cm in diameter, and thus represents a small control volume moving with a traveling bed. This sort of experiment gives valuable information about the ignition rate of the fuel, but the transient nature of the process makes it difficult to measure details of conditions inside the bed to support numerical modeling. Overfeed beds, on the other hand, run at more or less steady state, with a continual feed of fuel to maintain the bed height, giving them a structure very different from that of transient burning. This mode of operation is used in smaller scale biomass combustors and in gasifiers. Its steady state nature is an advantage for experimentation, allowing the measurement of concentrations in the bed and the analysis of samples of bed material. Despite this, there have been few recent experiments in overfeed beds,13-17 although there is a substantial body of much older literature on overfeed combustion of coal or coke.18 A number of computational models have also appeared, again mostly for the transient burning mode. Detailed reviews have recently been given by Di Blasi19 and by Yin et al.20 Most models treat the bed as a one-dimensional continuous porous medium: properties are assumed uniform in planes normal to the flow, and processes within the individual particles are ignored. The simplest of these calculate the ignition rate in the

1. Introduction Packed bed combustion is widely used for wood waste and other biomass combustion as well as for trash incineration. Essentially the same system is also used for gasification of biomass and other solid fuels. Although numerous recent experiments have been reported on the grate firing of wood, few give a detailed picture of events within the bed. This paper therefore presents detailed measurements of species concentrations, temperatures, and particle characteristics in a packed bed of wood burning in overfeed mode. A complete numerical model of char combustion developed earlier is extended by the addition of a simple model for pyrolysis and compared with the results of the experiments. A considerable body of literature on the combustion and gasification of wood and other solid biomass in packed beds has appeared within the past decade. Most experimental work has focused on a transient burn, in which the bed is ignited at the top and the flame is allowed to propagate downward while *To whom correspondence should be addressed. Telephone: 613-5625800 ext. 6281. Fax: 613-562-5177. E-mail: [email protected]. (1) Saastamoinen, J. J.; Taipale, R.; Horttanainen, M.; Sarkomaa, P. Combust. Flame 2000, 123, 214–226. (2) Horttanainen, M.; Saastamoinen, J.; Sarkomaa, P. Energy Fuels 2002, 16, 676–686. (3) Thunman, H.; Leckner, B. Fuel 2003, 82, 275–283. (4) Thunman, H.; Leckner, B. Fuel 2001, 80, 473–481. (5) R€ onnb€ ack, M.; Axel, M.; Gustavsson, L.; Thunman, H.; Leckner, B. Combustion processes in a biomass fuel bed - experimental results. In: Progress in Thermochemical Biomass Conversion; Bridgwater, A.V. Ed.; Blackwell Science: Oxford, 2001; pp 743-757. (6) Khor, A.; Ryu, C.; Yang, Y. B.; Sharifi, V. N.; Swithenbank, J. Fuel 2007, 86, 152–160. (7) Ryu, C.; Yang, Y. B.; Khor, A.; Yates, N. E.; Sharifi, V. N.; Swithenbank, J. Fuel 2006, 85, 1039–1046. (8) Yang, Y. B.; Sharifi, V. N.; Swithenbank, J. Fuel 2004, 83, 1553– 1562. (9) Yang, Y. B.; Yamauchi, H.; Nasserzadeh, V.; Swithenbank, J. Fuel 2003, 82, 2205–2221. (10) van der Lans, R. P.; Pedersen, L. T.; Jensen, A.; Glarborg, P.; Dam-Johansen, K. Biomass Bioenergy 2000, 19, 199–208. (11) Shin, D.; Choi, S. Combust. Flame 2000, 121, 167–180. (12) Tinaut, F. V.; Melgar, A.; Perez, J. F.; Horrillo, A. Fuel Process. Technol. 2008, 89, 1076–1089. r 2010 American Chemical Society

(13) Di Blasi, C.; Signorelli, G.; Portoricco, G. Ind. Eng. Chem. Res. 1999, 38, 2571–2581. (14) Bryden, K. M.; Ragland, K. W. Energy Fuels 1996, 10, 269–275. (15) Wiinikka, H.; Gebart, R. Energy Fuels 2004, 18, 897–907. (16) Oman, J.; Tacer, M.; Tuma, M. Bioresour. Technol. 1999, 67, 139–147. (17) Ryan, J. S.; Hallett, W. L. H. Chem. Eng. Sci. 2002, 57, 3873– 3882. (18) Cooper, J.; Hallett, W. L. H. Chem. Eng. Sci. 2000, 55, 4451– 4460. (19) Di Blasi, C. Prog. Energy Combust. Sci. 2008, 34, 47–90. (20) Yin, C.; Rosendahl, L. A.; Kær, S. K. Prog. Energy Combust. Sci. 2008, 34, 725–754.

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1,4

bed from heat transfer considerations alone. Most current models use complete numerical solutions of gas and solid phase species and energy conservation equations together with char oxidation and pyrolysis reactions.9-12,14,16-18,21-27 In some cases simplifications are made, such as combining the gas and solid energy equations10,21,27 or neglecting diffusion.12,14,16,22 One recent paper extends this sort of model to two dimensions to simulate a large inclined grate.28 The most complex models do not assume a continuum, but rather integrate a detailed model for individual particles into the bed calculation;3,29-33 all such models to date are for the transient burning mode rather than steady overfeed combustion. Most models use a single reaction to describe pyrolysis kinetics,9,12,22,24,26-31,33 but a few have employed multistep kinetics.11,23,25,32 Much of the knowledge of combustion, gasification, and pyrolysis required for these models comes from the many recent studies, both experimental and numerical, on the conversion of single biomass particles. This body of work was recently thoroughly reviewed by Di Blasi19 and will not be further treated here. In view of the lack of recent work on overfeed combustion, and considering the greater opportunities that this system presents for detailed measurements and comparisons between experiment and theory, this paper focuses on both experiments and computational modeling for the overfeed mode.

Figure 1. Diagram of fuel particle. For dimensions see Table 1.

The void fraction of a sample bed was measured by water displacement, the particles first being wetted to avoid errors due to water absorption by the dry wood. It is well-known that the void fraction at the wall of a packed bed is larger than in the interior. The effects of this anomaly are considered to be negligible for a vessel to particle diameter ratio of 10 or more,34-37 but the particles used here fall slightly below this limit. To reduce uncertainty due to wall effects, the void fraction was therefore measured in a container of the same diameter as the combustor, and accordingly represents an average over the cross-section. The reproducibility of packing is an issue in packed bed research: in these experiments, the particles were thrown randomly onto the top surface of the bed, and the same method was used to create the bed for void fraction measurement. A light tamping of the burning bed was done from time to time to preclude bridging or the formation of large voids. The fuel was allowed to acclimatize to the lab environment for a couple of weeks after the particles had been cut; as the experiments were conducted indoors in the winter time, this resulted in low values of fuel moisture. Table 1 summarizes properties of the fuel and the operating conditions of experiments, including ASTM proximate analyses. Experiments with the same identifier were intended to be replicates, although in some cases minor variations in fuel particle dimensions occurred between different shipments of lumber. Material from the bed was analyzed for particle size and density by performing individual particle size and weight measurements and an ASTM proximate analysis on a representative sample from each slice (usually 7-10 particles). To get an average sample from partially pyrolyzed pieces of wood, particles were cut in half, mounted in a lathe, and faced off across the cross-section, the resulting swarf being collected for the ASTM test. Since tar is a major product of pyrolysis, it was desired to sample it as well as the gaseous species at a number of different locations in the bed. To the best of the authors’ knowledge, this has not been done before, all previous measurements of tar in the literature being confined to the sampling of product gases at the exit of gasifiers.13,38,39 For local sampling, therefore, a novel probe was devised (Figure 2) that condenses and collects tar in situ in a water-cooled porous metal filter element. A metered flow of gas is drawn through the probe for a measured time interval, and the tar mass collected is determined from the weight gain of the filter element. The filters are held in a tapered split sleeve of brass, similar to a lathe or milling machine collet, which is closed and sealed around the filter by pressure from a threaded cap, all parts being machined to a close fit to avoid gas leakage past the filter. The probe tip was designed for good heat conduction from the filter to the cooling water, ensuring full condensation of any tar. Two filter elements are used, the second being a backup to collect any tar penetrating through the first. As protection against tar deposits for the rest of the sampling system, the gas leaving the probe passes through an impinger flask filled with methanol and cooled with ice water. The gas then flows to

2. Experiments Experiments were conducted in a packed bed combustor of 23 cm internal diameter operated in overfeed combustion mode, with fresh fuel being fed to the top of the bed at frequent regular intervals to maintain a constant bed depth and air introduced through the bottom in counterflow to the fuel motion. Secondary air was introduced above the bed to burn off volatiles and CO, but had no influence on the bed itself beyond heat transfer from the volatiles flame. Type B bare wire thermocouples inserted radially into the bed measured local temperatures. A water-cooled gas sampling probe inserted vertically into the bed withdrew samples at roughly isokinetic sampling rates. Samples were analyzed in a gas chromatograph using a Carboxen 1000 column for O2, N2, CO, CO2, and CH4. At the conclusion of the run the bed was lowered and cut into measured slices for analysis. More details are given by Ryan and Hallett.17 The fuel was 1  2 in. nominal size (roughly 19  38 mm actual size) spruce lumber cut into parallelepipeds (Figure 1). Use of a regular particle shape, rather than, for example, wood chips, allowed precise calculation of particle equivalent diameter and sphericity for later numerical modeling. This particular shape was chosen to ensure random packing, as initial trials showed that cubic or rectangular particles tended to pack in regular layers. (21) Gort, R.; Brouwers, J. J. H. Combust. Flame 2001, 124, 1–13. (22) Kær, S. K. Biomass Bioenergy 2005, 28, 307–320. (23) Yang, Y. B.; Ryu, C.; Khor, A.; Yates, N. E.; Sharifi, V. N.; Swithenbank, J. Fuel 2005, 84, 2116–2130. (24) Zhou, H.; Jensen, A. D.; Glarborg, P.; Jensen, P. A.; Kavaliauskas, A. Fuel 2005, 84, 389–403. (25) Di Blasi, C. Chem. Eng. Sci. 2000, 55, 2931–2944. (26) Yang, W.; Ponzio, A.; Lucas, C.; Blasiak, W. Fuel Process. Technol. 2006, 87, 235–245. (27) Fatehi, M.; Kaviany, M. Combust. Flame 1994, 99, 1–17. (28) Yang, Y. B.; Newman, R.; Sharifi, V.; Swithenbank, J.; Ariss, J. Fuel 2007, 86, 129–142. (29) Yang, Y. B.; Ryu, C.; Khor, A.; Sharifi, V. N.; Swithenbank, J. Fuel 2005, 84, 2026–2038. (30) Peters, B. Combust. Flame 2002, 131, 132–146. (31) Bruch, C.; Peters, B.; Nussbaumer, T. Fuel 2003, 82, 729–738. (32) Wurzenberger, J. C.; Wallner, S.; Raupenstrauch, H.; Khinast, J. G. AIChE J. 2002, 48, 2398–2411. (33) Johansson, R.; Thunman, H.; Leckner, B. Combust. Flame 2007, 149, 49–62.

(34) Mehta, D.; Hawley, M. C. Ind. Eng. Chem. Process Design Develop. 1969, 8, 280–282. (35) Di Felice, R.; Gibilaro, L. G. Chem. Eng. Sci. 2004, 59, 3037– 3040. (36) Eisfeld, B.; Schnitzlein, K. Chem. Eng. Sci. 2001, 56, 4321–4329. (37) Nemec, D.; Levec, J. Chem. Eng. Sci. 2005, 60, 6947–6957. (38) Hasler, P.; Nussbaumer, T. Biomass Bioenergy 2000, 18, 61–66. (39) Carpenter, D. L.; Deutch, S. P.; French, R. J. Energy Fuels 2007, 21, 3036–3043.

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Table 1. Fuel Properties and Experimental Conditions experiment identifier 2

primary air mass flux (kg/m hr) particle size (vol. equiv. diameter) (cm) particle sphericity particle dimensions (see Figure 1): a (cm) b (cm) c (cm) θ () particle density (kg/m3) (dry basis) fuel volatiles (ASTM, dry basis) fuel fixed carbon (dry basis) fuel moisture (dry basis) ash (dry basis) bed height (cm) bed void fraction average measured burning rate, dry fuel (kg/m2hr)

A1D2a

A1D2b

A2D2

A1D3a

A1D3b

108 2.81 0.76

108 2.81 0.76

130 2.72 0.77

108 3.42 0.76

108 3.35 0.76

3.50 1.80 1.85 25 525 84.1% 15.7% 6% 0.2% 22 0.47 71.3

3.50 1.80 1.85 25 500 84% 15.7% 6% 0.3% 22 0.47 74

3.0 1.85 1.9 25 492 84.1% 15.7% 6% 0.2% 22 0.47 105

4.00 2.60 2.00 20 457 83.5% 16.4% 10% 0.1% 22 0.47 67.3

3.85 2.80 1.85 20 535 84.1% 15.4% 7% 0.5% 22 0.47 65

was extended to include a simple treatment of pyrolysis. This is a one-dimensional continuous porous medium model, originally developed for combustion of char (carbon), and includes all relevant processes: gas-phase and solid surface reactions, fuel particle consumption, shrinkage and motion, ash layer buildup, heat conduction in the solid phase, heat conduction and species diffusion in the gas phase, heat and mass transfer between the particulate and gas phases, properties variations, the effects of ash particles in the voids between fuel particles on heat and mass transfer, and the effects of thermal boundary conditions such as the grate and the freeboard space above the bed. It can also account for nonspherical fuel and ash particles. The governing equations are solved by finite volume techniques to give the details of gas and solid composition, temperature, and particle properties as functions of position and time. Although the processes being considered are nearly steady state, the accumulation of ash can cause slow variations with time, hence a fully transient solution is generated. For the present work this model was extended to include pyrolysis of the fuel by adding a one-step first-order homogeneous pyrolysis reaction to the solid phase. This is the simplest possible model of pyrolysis: it ignores the role that internal heat transfer can play in the pyrolysis of larger fuel particles, and it reduces the complex kinetics of pyrolysis to a single reaction. The fuel is assumed to pyrolyze with a char yield of ζC: 1 kg of fuel f ζC kgðchar þ ashÞ þ ð1 -ζC Þ kg of volatiles

Figure 2. Cross-section of tip of tar probe.

the gas chromatograph for analysis. Like the gas sampling probe, the tar probe is inserted vertically downward into the desired sampling location in the bed. Potential errors in tar probe samples include the collection of extraneous tar before and after the actual sampling period and failure to condense part of the tar in the sampled stream. The first is avoided by backflushing the probe with nitrogen as it is moved to the sampling location before sampling begins, and by withdrawing it from the bed as quickly as possible after sampling ends. To ensure a high tar collection efficiency, the sampling time was kept short enough to keep the second filter element almost tarfree, typically about 5 min at a gas sampling rate of 0.5 g/min. Any samples showing breakthrough of tar into the second filter were rejected. Discoloration of the methanol in the impinger flask provided an immediate visual indication of any breakthrough. A simple numerical model of heat transfer in the probe tip and filter elements indicated that gas sampled at 1000 C would exit the filters at 100-150 C, so that all but fairly light vapors could be expected to condense. Since the fuel particles are fairly large, pyrolysis takes place under slow heating conditions, which favor secondary reactions and the production of heavier species.19 Condensation of any product water was prevented by maintaining the probe cooling water at about 50 C. The alternative to condensing the tar would have been a probe heated to 300400 C to maintain the tar in a vapor state; however, the higher temperatures would probably cause secondary decomposition of the tar and consequent deposition of coke in transit through the probe, and the bulk and complexity of such a probe would cause a major disturbance to the flow in the bed.

The pyrolysis products are assumed to consist of fixed proportions χCO2, χCO, χCH4, and χT of CO2, CO, CH4, and tar vapor, respectively. Since drying in an overfeed bed takes place at the very top of the bed, and hence has little effect on other bed processes, fuel moisture and drying are neglected, an assumption also justified by the low moisture content (6%) of the fuel used in the experiments. Combustion of pyrolysis products is assumed to occur entirely above the bed and is therefore not included in this model. This assumption is valid for all but very thin overfeed beds, since all of the oxygen in the primary air is normally consumed near the grate (see Results, later); however, it does not hold for the transient burning mode which has been the object of most recent studies.1-12 Pyrolysis products must be added to the conservation equations for the gas and solid phases in the bed. The local rate of evolution of pyrolysis products per unit bed volume is rP ¼ ð1 -εÞXF ð1 -ζC ÞFF0 AP YW expð -EP =RTÞ ðkg=m3 sÞ ð1Þ where YW is the mass fraction of unconverted wood in the fuel. The continuity equation for the gas phase as a whole is D D ðεF Þ þ ðFG vG Þ ¼ GaBF þ rP ð2Þ Dt G Dx

3. Computational Modeling In parallel with the experiments, the packed bed combustion model developed by Cooper and Hallett18 and Ryan and Hallett17 1586

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reaction or quantity reduction: C þ CO2 f 2CO particle pore characteristics for CO2 reduction30,44 pyrolysis: fuel f volatiles þ char enthalpy of pyrolysis volatiles yield (1 - ζC) volatiles composition by mass

rate or value GCO2 = ApCO2 exp(-E/RT), with A = 0.02 kg/m2 s kPa, E = 200 kJ/gmol. G is based on particle internal surface area. εP = 0.6; τ = 1; aI = 3  107 m2/m3 particle volume eq 1, with AP = 0.015 s-1, EP = 20 kJ/gmol 300 kJ/kg wood (endothermic) volatiles fraction from ASTM proximate analysis (Table 1) 35% CO, 10% CO2, 6% CH4, balance tar

Cooper and Hallett.18 This equation is used to solve for the surface concentration of O2 and other gases, which in turn serve as inputs for the char oxidation and reduction reactions. Char conversion can occur during pyrolysis if O2 or CO2 is present at the solid surface. Properties are required for wood, char, and tar vapor. Correlations for specific heat were taken from Groe nli and Melaaen40 for wood and from Larfeldt et al.41 for char, while thermal conductivities were taken from Koufopanos et al.42 for wood and Groe nli and Melaaen40 for char. A useful compilation of wood and char properties was recently given by Gupta et al.43 The tar was assumed to have the properties of levoglucosan,19 a common high molecular weight product of cellulose pyrolysis, and properties for it—vapor specific heat, diffusivity, and conductivity— were estimated using standard correlations,44 as were properties of the other gases.18 The ash released from char conversion was assumed to separate from the fuel particles and to accumulate as a separate phase in the interstices between particles. This corresponded to the behavior observed in the bed samples from the present experiments; only rarely were particles seen with a surface layer of ash. The effects of this on heat and mass transfer in the bed were accounted for using the ash model of Ryan and Hallett.17 The required ash properties were taken from some earlier wood combustion tests:45 these gave a mean particle diameter of 1 mm, determined by sieve analysis; a void fraction for the ash phase by itself of 0.45, determined by water displacement; a sphericity of 0.60, determined by permeametry (pressure loss measurement in an ash bed); and a particle density of 1030 kg/m3. Details of the reaction kinetics used are given in Table 2. Rate parameters were selected to give a reasonable fit to experimental data, although no rigorous fitting procedure was used. For the char reduction reaction, it was necessary to allow for internal reaction in the particle pores through a calculation of particle effectiveness,17 since for the temperature range encountered here the effectiveness proves to be fairly high (0.5 or greater). This requires estimation of particle porosity εP, pore tortuosity τ, and internal surface area aIG (m2/g). The numbers for εP and τ in Table 2 are taken from those of Peters30 for fir wood; Larfeldt et al.41 report the same εP for the macro-porosity of birch char. The value of aIG comes from measurements of Cetin et al.46 for pine char generated under slow heating conditions, and is similar to those cited for coal char (range 50-200 m2/g47,48). The value of

where G is the rate of char consumption by oxidation and CO2 reduction, and aBF is the specific surface area of fuel particles in m2/m3 bed volume. The rate of production of each individual product species is rCO2 = χCO2rP, rCO = χCOrP, etc., so that, for example, the transport equation for tar is   D D D DYT ðεFG YT Þ þ ðFG vG YT Þ ¼ FG DT;eff þ rT ð3Þ Dt Dx Dx Dx where DT,eff is the effective diffusivity of tar, accounting for the significant but often neglected phenomenon of back-diffusion in the bed.18 Analogous equations are written for the other gases. The solids in the bed comprise two phases, the fuel particles (consisting of unconverted wood plus char and ash) and the ash released by char conversion. For fuel and ash together, the overall continuity equation is D D ½F ð1 - εÞ þ ðFS vS Þ ¼ -GaBF - rP ð4Þ Dt S Dx where vS is the superficial velocity of the solid phase in bulk. For the fuel particles alone (i.e., without the ash fraction R), mass conservation gives D D ½F XF ð1 - εÞ þ ðFF vF Þ ¼ -GaBF ð1 þ RÞ - rP ð5Þ Dt F Dx The velocities from these are required for the particle diameter and solids energy equations.17,18 A third solids conservation equation tracks the extent of pyrolysis through the local mass fraction YW of unpyrolyzed fuel: D D rP ð6Þ ½F XF YW ð1 - εÞ þ ðFF vF YW Þ ¼ 1 -ζC Dt F Dx The solid and gas phase energy equations18 must also be modified to account for the efflux of pyrolysis products, the term (-GPaBFΔHP) being added to the solid phase equation and the term (GPaBFhP) being added to the gas equation, where ΔHP is the enthalpy of pyrolysis and hP is the enthalpy of the gaseous products. During pyrolysis, the fuel particle size is assumed constant, the mass loss being reflected solely in the decreasing density. This is of course an approximation, which is compounded by the fact that wood is quite anisotropic; however, this model has been used by others11,12,24,25,31,32 and will be justified by experimental results shown later. During char conversion, however, the char density is assumed constant and the particle is allowed to shrink. These assumptions fix the char density as FC = ζCFF0, where FF0 is the initial fuel density, and the density of partially converted fuel is then

(40) Gro e nli, M. G.; Melaaen, M. C. Energy Fuels 2000, 14, 791–800. (41) Larfeldt, J.; Leckner, B.; Melaaen, M. C. Biomass Bioenergy 2000, 18, 507–514. (42) Koufopanos, C. A.; Papayannakos, N.; Maschio, G.; Lucchesi, A. Can. J. Chem. Eng. 1991, 69, 907–915. (43) Gupta, M.; Yang, J.; Roy, C. Fuel 2003, 82, 919–927. (44) Reid, R. C.; Prausnitz, J. M.; Poling, B. E. The Properties of Gases and Liquids, 4th ed.; McGraw-Hill: New York, 1987. (45) Ryan, J. S.; Hallett, W. L. H.; Di Iorio, J. Experiments on solid fuel combustion in an overfeed bed, Canadian Section 1999 Spring Technical Meeting; Combustion Inst.: 1999; p 99-21-1 - 99-21-6 (46) Cetin, E.; Moghtaderi, B.; Gupta, R.; Wall, T. F. Fuel 2004, 83, 2139–2150. (47) Valix, M. G.; Trimm, D. L.; Smith, I. W.; Harris, D. J. Chem. Eng. Sci. 1992, 47, 1607–1617. (48) Smith, I. W. The Combustion Rates of Coal Chars: A Review. 19th Symposium (International) on Combustion, 1982; pp 1045-1065.

FF ¼ ½YW =FF0 þð1 - YW Þ=FC  -1 ¼ FF0 ζC =½1 -ð1 - ζC ÞYW  ð7Þ Because of mass transfer associated with solid surface reactions and the efflux of volatiles, gas concentrations at the particle surface differ from those in the free stream. These concentrations can be determined by writing the net flux of each species i from the surface as the sum of convection and diffusion: Gi ¼ ðG þ GP ÞYiR þ kYi ðYiR - Yi¥ Þ ðkg=m2 sÞ

ð8Þ

where GP = rP/aBF is the flux of pyrolysis gas from the surface, and kYi is the mass transfer coefficient, calculated as described by 1587

Energy Fuels 2010, 24, 1584–1591

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E was assumed based on the literature for biomass chars, while A was chosen to reproduce the behavior of measured CO and CO2 concentrations in the bottom 10 cm of the bed, where pyrolysis had essentially ceased. For pyrolysis, reported activation energies are typically of the order of EP = 200-250 kJ/mol for cellulose,19,52 with values ranging down to about 100 for other wood components or for wood as a whole.19,25,29,32,40,42,53-55 However, for the fairly large particles employed here, intraparticle heat conduction is as important as kinetics, and EP therefore represents an effective value that is substantially lower than the intrinsic one; reported values range from 16 to 30 kJ/mol.19,55 The assumed pyrolysis product composition is based on elemental mass balances on the products at the bed exit, with adjustments to better fit the measurements. The enthalpy of pyrolysis is taken from the detailed study of Rath et al.;56 the particular number chosen represents the primary pyrolysis reaction of spruce at low char yields. The other two chemical reactions—char oxidation and gas-phase CO oxidation—were dealt with exactly as in earlier work.17,18 Char oxidation was essentially diffusion-controlled (particle effectiveness on the order of 0.001), and so was assumed to occur exclusively on the particle surface. The calculation domain for the model extended through the grate, which was modeled in detail as described by Cooper and Hallett,18 but the results shown here start from the top surface of the grate. Boundary conditions at the top were treated as described by Ryan and Hallett,17 and an effective radiating temperature of 700 K was used to represent an average of the effects of the water-cooled chamber walls and the radiation from the volatiles flame above the bed. This number was based on measurements of temperatures above the bed using two thermocouples of two different sizes to discriminate between radiation and convection.

Figure 3. Mass fractions of gases and tar in the bed as functions of height above the grate for conditions of experiments A1D2a, b (2.81 cm particles, air flux 108 kg/m2h). Units are g/g of dry gas without tar. Points are measurements, with open symbols for experiment A1D2a and solid symbols for A1D2b; lines are predictions. Key to symbols: 2 O2, b CO, 9 CO2, ) CH4, and 1 tar.

4. Results Figures 3-5 show concentrations of various gas species and tar as a function of vertical distance above the grate. The O2, CO, and CO2 profiles show the typical behavior of overfeed combustion: all of the oxygen is consumed by char oxidation within the first 1.5 particle diameters above the grate, producing CO at the particle surface which then rapidly oxidizes to CO2. (This is quite unlike the behavior of beds undergoing transient burning from the top, in which oxygen is available for char and volatiles combustion throughout much of the bed.) After depletion of the oxygen, any further char consumption takes place by reduction of CO2, so that CO levels rise and CO2 levels fall as one moves further up the bed. These events and the concentration profiles they produce are almost identical to those observed in char beds.17,18 Pyrolysis takes place within the top 10 cm or so of the bed, producing tar and CH4 as well as adding to the already existing CO and CO2. The measurements show considerable scatter, and the main cause of this is stochastic variations in local conditions. The bed consists of fairly large particles and so is not really a con-

Figure 4. Mass fractions of gases and tar in the bed as functions of height above the grate for conditions of experiment A2D2 (2.81 cm particles, air flux 130 kg/m2h). Units are g/g of dry gas without tar. Points are measurements, lines are predictions. Key to symbols: 2 O2, b CO, 9 CO2, ) CH4, and 1 tar.

(49) Di Blasi, C. Prog. Energy Combust. Sci. 2009, 35, 121–140. (50) Struis, R. P. W. J.; von Scala, C.; Stucki, S.; Prins, R. Chem. Eng. Sci. 2002, 57, 3581–3592. (51) Khalil, R.; V arhegyi, G.; J€aschke, S.; Gro e nli, M. G.; Hustad, J. Energy Fuels 2009, 23, 94–100. (52) Gro e nli, M. G.; Antal, M. J.; Varhegyi, G. Ind. Eng. Chem. Res. 1999, 38, 2238–2244. (53) Di Blasi, C.; Branca, C. Ind. Eng. Chem. Res. 2001, 40, 5547– 5556. (54) Lu, H.; Robert, W.; Peirce, G.; Ripa, B.; Baxter, L. L. Energy Fuels 2008, 22, 2826–2839. (55) Thunman, H.; Leckner, B.; Niklasson, F.; Johnsson, F. Combust. Flame 2002, 129, 30–46. (56) Rath, J.; Wolfinger, M. G.; Steiner, G.; Krammer, G.; Barontini, F.; Cozzani, V. Fuel 2003, 82, 81–91.

Figure 5. Mass fractions of gases and tar in the bed as functions of height above the grate for conditions of experiments A1D3a, b. (3.42 or 3.35 cm particles, air flux 108 kg/m2h). Units are g/g of dry gas without tar. Points are measurements, with open symbols for experiment A1D3a and solid symbols for A1D3b; lines are predictions for experiment A1D3b (3.35 cm particles). Key to symbols: 2 O2, b CO, 9 CO2, ) CH4, and 1 tar.

tinuum: local conditions as sensed by the probe can vary substantially depending on the orientation of nearby particles with respect to the probe. This is particularly true of particles undergoing pyrolysis near the top of the bed, and is the 1588

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Figure 7. Particle diameters and densities as functions of height above the grate for conditions of experiments A1D2a, b (2.81 cm particles, air flux 108 kg/m2h). Points are measurements, located at the center of each slice taken from the bed, with open symbols for experiment A1D2a and solid symbols for A1D2b; lines are predictions. Key to symbols: O diameter (left axis), 0 density (right axis). Figure 6. Predicted solid and gas temperatures (lines) and measured temperatures (points) in the bed as functions of height above the grate. Top set of curves: conditions of experiment A1D2b, with open symbols for measurements from experiment A1D2a and solid symbols for A1D2b. Middle: conditions of experiment A2D2. Bottom: conditions of experiment A1D3b; open symbols for A1D3a, solid symbols for A1D3b.

the assumed tar proportion in the volatiles, but this would increase CO and/or CO2 levels well above the measured values. Elemental mass balances on the process consistently showed a deficiency of hydrogen in the products, suggesting that the discrepancy is most likely due to the fact that water vapor and H2 are not captured by any of the instrumentation. Only limited data are available on the amount of water produced by wood pyrolysis, because it is usually not separated from the other liquid products (tar or bio-oil), but it has been reported as about 4-5% of the original fuel mass32,57 or as about equal to the CO2 quantity produced,56 sufficient to account for the discrepancy. Hydrogen levels as high as 2% of the original wood have been reported,57 but most sources give fractions well under 1%,13,32,57,60 so that there should be little error in neglecting it. Reported levels of these and other products vary widely depending on process conditions. Tar or liquid yields cited range from about 30 to 65%,13,32,38,57,60 while CO levels are variously reported as less than 10%,13,32,57,60 as 40% (under rapid heating),59 or as 2.5-3.5 times the CO2 yield.58 The pyrolysis product composition assumed here (Table 2) has more CO and less tar than generally cited in the literature, which can be attributed to secondary decomposition of tar both in the bed and in the pores of the fuel particles. Changes in the pyrolysis reaction rate parameters increased or decreased the depth of the pyrolysis zone as the reaction got respectively slower or faster, but did not materially affect the exit gas concentrations. Figures 7-9 give mean particle sizes and densities as measured from the slices taken from the bed at the end of the experiment, while Figures 10-12 give ASTM volatiles and ash contents for the same slices. The measured points are plotted at the midpoint of each slice. The model assumes constant volume pyrolysis followed by char conversion at constant char density, and this behavior is clearly reflected in the predicted particle sizes and densities. (The predicted gradual decrease in particle diameter in the pyrolysis zone is due to char conversion, which can begin while pyrolysis is still

reason why the tar measurements show more scatter than the others. The temperatures (Figure 6) show a peak just downstream of the oxidation zone at the bottom of the bed, and thereafter drop continuously owing to the endothermic character of the reduction and pyrolysis reactions. Gas temperatures are substantially higher than solid temperatures through most of the bed, the result of the highly exothermic CO oxidation reaction at the bottom. Measured temperatures can be expected to reflect solid rather than gas temperatures because of the intense thermal radiation between particles, and the data here are indeed close to the predicted solid temperatures. Increasing the particle size (compare Figure 5 with Figures 3 and 4, also the individual sets of curves in Figure 6) shifts both temperature and concentration profiles downstream in proportion. This agrees with earlier work showing that packed beds scale roughly with the particle size.17,18 Increasing the air flow rate (c.f., Figures 3 and 4) does not materially change the concentration profiles, but the burning rate increases in direct proportion (Table 1), and this raises both solid and gas temperatures (Figure 6) owing to the higher reaction density in the bed. The progress of pyrolysis as reflected in the CH4 concentration is similar for the two air flow rates, but the measured tar levels are lower for the higher rate, suggesting more rapid secondary pyrolysis reactions brought on by the higher temperatures. Model results are included in all graphs of experimental data. Those for gas concentrations and temperatures were generated for a time of two hours after the start of the experimental run, while those for bed properties are at the end of the run (total duration 4-5 h). Since the ash fraction of the fuel is low, the effects of ash buildup on the bed are small, and the procedure used in earlier work17 for matching predictions with measurements at the same time was not used. Predicted gas concentrations and temperatures (Figures 3-6) agree well with measured values apart from the scatter in the measurements. The exception is tar, which is consistently higher than measured. This could be corrected for by reducing

(57) Ranzi, E.; Cuoci, A.; Faravelli, T.; Frassoldati, A.; Migliavacca, G.; Pierucci, S.; Sommariva, S. Energy Fuels 2008, 22, 4292–4300. (58) Thunman, H.; Niklasson, F.; Johnsson, F.; Leckner, B. Energy Fuels 2001, 15, 1488–1497. (59) Couhert, C.; Commandre, J.-M.; Salvador, S. Fuel 2009, 88, 408– 417. (60) Di Blasi, C.; Branca, C.; Santoro, A.; Gonzalez Hernandez, E. Combust. Flame 2001, 124, 165–177.

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Figure 11. Fractions of ash and ASTM volatiles per unit mass of dry fuel as functions of height above the grate for conditions of experiment A2D2 (2.81 cm particles, air flux 130 kg/m2h). Points are measurements, located at the center of each slice taken from the bed, lines are predictions. Key to symbols: 1 volatiles, 0 ash.

Figure 8. Particle diameters and densities as functions of height above the grate for conditions of experiment A2D2 (2.81 cm particles, air flux 130 kg/m2h). Points are measurements, located at the center of each slice taken from the bed, lines are predictions. Key to symbols: O diameter (left axis), 0 density (right axis).

Figure 12. Fractions of ash and ASTM volatiles per unit mass of dry fuel as functions of height above the grate for conditions of experiments A1D3a, b. (3.42 or 3.35 cm particles, air flux 108 kg/ m2h). Points are measurements, located at the center of each slice taken from the bed, with open symbols for experiment A1D3a and solid symbols for A1D3b; lines are predictions for experiment A1D3b (3.35 cm particles). Key to symbols: 1 volatiles, 0 ash.

Figure 9. Particle diameters and densities as functions of height above the grate for conditions of experiments A1D3a, b. (3.42 or 3.35 cm particles, air flux 108 kg/m2h). Points are measurements, located at the center of each slice taken from the bed, with open symbols for experiment A1D3a and solid symbols for A1D3b; lines are predictions for experiment A1D3b (3.35 cm particles). Key to symbols: O diameter (left axis), 0 density (right axis).

spread of measured particle sizes, as indicated by the bars, is large enough that it would be difficult to construct a more accurate model for particle shrinkage from these data. An overall test of the constant volume pyrolysis/constant density char approximation is provided by the char density at the bottom of the bed, which if this model is correct should equal the product of initial fuel density and (fixed carbon þ ash), or (from Table 1) about 75 - 85 kg/m3. The measured values are in fact only slightly larger than this, lending support to this approximation. The volatiles content shows the expected pattern of decreasing rapidly in the pyrolysis zone, while ash is seen to accumulate at the bottom of the bed (Figures 10-12). The model assumes that the volatiles yield from pyrolysis is equal to the ASTM value, and the agreement between the predicted and measured volatiles contents from the bed samples suggests that this is reasonable. Although the volatiles yield can vary widely depending on process conditions, the ASTM test conditions of slow heating are close to those experienced by large particles in a bed, and the numbers also agree with char yields measured by others under slow heating/high temperature conditions.13,32,58,60 Some error in the solids sampling is possibly due to the fact that pyrolysis (unlike char conversion) does not cease instantaneously when the bed is quenched with nitrogen. Taking a temperature of 300 C as the lower limit for

Figure 10. Fractions of ash and ASTM volatiles per unit mass of dry fuel as functions of height above the grate for conditions of experiments A1D2a, b (2.81 cm particles, air flux 108 kg/m2h). Points are measurements, located at the center of each slice taken from the bed, with open symbols for experiment A1D2a and solid symbols for A1D2b; lines are predictions. Key to symbols: 1 volatiles, 0 ash.

in progress.) The measured mean particle diameters lie slightly below the predictions, suggesting that there is in fact a small amount of particle shrinkage during pyrolysis. However, the 1590

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cellulose pyrolysis, temperature records during quenching showed that the upper part of the bed took about 3 min to cool to that level. This may explain differences between predicted and measured volatiles in the upper part of the bed.

v = velocity, m/s XF = volume fraction of fuel in the solid phase Y = mass fraction YW = mass fraction unconverted wood in fuel

5. Conclusions

Greek

The measurements presented here show that an overfeed packed bed operated at steady state can yield useful details of gas composition, temperature, particle properties, and bed structure not accessible in transient experiments. A novel probe for the in situ measurement of tar concentrations in the bed has been developed and found to give credible measurements. The detailed numerical model for packed bed combustion gives good predictions of the experimentally measured quantities. The simple one-step reaction model for pyrolysis gives satisfactory results; its rate parameters and product yields must of course be fitted to experiments, but the resulting fitted quantities are credible when compared to equivalent data from the literature.

R = ash mass fraction in fuel ε = void fraction εP = particle porosity ζC = char yield (mass fraction) F = density, kg/m3 FF0 = initial density of fuel (wood), kg/m3 τ = particle pore tortuosity χi = mass fraction of species i in pyrolysis products Subscripts B = bed C = char F = fuel (i.e., wood þ char) G = gas i = individual species I = internal to particle P = pyrolysis reaction R = at particle surface S = solid phase (fuel þ ash) T = tar 0 = initial value ¥ = freestream value (far from surface)

Nomenclature a = specific surface area, m2/m3 A = pre-exponential factor, s-1 dP = particle diameter, m E = activation energy, J/mol G = mass flux of products from carbon conversion, kg/(m2 s) Gi = mass flux of species i, kg/(m2 s) ΔHP = enthalpy of pyrolysis, kJ/(kg original fuel) kYi = mass transfer coefficient for species i, kg/(m2 s) r = reaction rate, kg/(m3 bed s) R = universal gas constant, 8.314 J/(mol K) T = temperature, K

Acknowledgment. The authors gratefully acknowledge the financial support of a Discovery Grant from the Natural Sciences and Engineering Research Council, Canada.

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